On Educational psychology: A cognitive view.

The third way: the renewal of social democracy

Abstract Student satisfaction is important in the evaluation of distance education courses as it is related to the quality of online programs and student performance. Interaction is a critical indicator of student satisfaction; however, its impact has not been tested in the context of other critical student- and class-level predictors. In this study, we tested a regression model for student satisfaction involving student characteristics (three types of interaction, Internet self-efficacy, and self-regulated learning) and class-level predictors (course category and academic program). Data were collected in a sample of 221 graduate and undergraduate students responding to an online survey. The regression model was tested using hierarchical linear modeling (HLM). Learner–instructor interaction and learner–content interaction were significant predictors of student satisfaction but learner–learner interaction was not. Learner–content interaction was the strongest predictor. Academic program category moderated the effect of learner–content interaction on student satisfaction. The effect of learner–content interaction on student satisfaction was stronger in Instructional Technology and Learning Sciences than in psychology, physical education or family, consumer, and human development. In sum, the results suggest that improvements in learner–content interaction yield most promise in enhancing student satisfaction and that learner–learner interaction may be negligible in online course settings.

Interaction, Internet Self-Efficacy, and Self-Regulated Learning as Predictors of Student Satisfaction in Distance Education Courses.

Student satisfaction is important in the evaluation of distance education courses as it is related to the quality of online programs and student performance. Interaction is a critical indicator of student satisfaction; however, its impact has not been tested in the context of other critical student- and class-level predictors. In this study, we tested a regression model for student satisfaction involving student characteristics (three types of interaction, Internet self-efficacy, and self-regulated learning) and class-level predictors (course category and academic program). Data were collected in a sample of 221 graduate and undergraduate students responding to an online survey. The regression model was tested using hierarchical linear modeling (HLM). Learner–instructor interaction and learner–content interaction were significant predictors of student satisfaction but learner–learner interaction was not. Learner–content interaction was the strongest predictor. Academic program category moderated the effect of learner–content interaction on student satisfaction. The effect of learner–content interaction on student satisfaction was stronger in Instructional Technology and Learning Sciences than in psychology, physical education or family, consumer, and human development. In sum, the results suggest that improvements in learner–content interaction yield most promise in enhancing student satisfaction and that learner–learner interaction may be negligible in online course settings.

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Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses

Apart from technology: understanding people’s non-use of information and communication technologies in everyday life

Distance learning is different from regular learning in the classroom. One of the main factors which influence the effectiveness of the learning process is the interaction that exists between the teacher and the student. Our research indicates that different interactions have different effects. There are two methods used for implementing distance learning systems, i.e. synchronous and asynchronous. Our research is based on the model developed by Oliver and McLaughlin. According to this model, there exist five types of teacher-student interactions: social, procedural, expository, explanatory and cognitive. The present study refers to the cognitive interaction and differentiates between surface processes and deep processes. The study presents different variables and their influences on the students' achievements and their satisfaction from learning via a synchronous versus an asynchronous distance learning system. The interaction level between the students and the teacher and among the students was found to be a significant factor in determining the effectiveness of the teaching method. The observations and interviews which we held with the students helped clarify the information that was obtained using the quantitative research tools, and showed that the presence of a teacher-student interaction which accompanies the learning process is very important for all learners. However, students with high-level thinking can overcome the low-level of interactions in asynchronous learning.

http://www.anitacrawley.net/Resources/Articles/Offir2008%20deep%20learning%20syn%20vs%20asy.pdf

Surface and deep learning processes in distance education: Synchronous versus asynchronous systems

This paper describes a distance learning project that enables talented high school students in geographically isolated and underdeveloped areas to participate in an introductory university course without leaving the supportive framework of their high schools. The rationale behind the project is described as well as a model in which university faculty work together with high schools in order to achieve broad educational goals. The online collection of student-related data is described, together with how this helped us to identify and solve problems experienced by high school students in a distance learning environment. The collection and implementation of teacher-related data used in order to increase the effectiveness of instruction during the course is described. Finally, some significant results of this research are presented, with a description of how they can be implemented not only to solve but also to prevent potential obstacles to effective distance learning in future projects.

Teacher–student interactions and learning outcomes in a distance learning environment

Although difficulties that characterize distance learning (DL) clearly have differential effects on different learners, links between barrier research and individual differences remain relatively unexplored. This study examined the relationship between cognitive style, based on Jung's (1971) theory, and achievement levels among 77 university students in a videoconference-based learning environment. Clarifying this relationship enables educators to identify in advance students who may require additional instructional support in a DL context. Understanding student-related variables that affect learning also enables faculty to adapt instructions to meet the diverse needs of different students instead of adopting a “one-size-fits-all” approach to designing DL environments.

Introverts, Extroverts, and Achievement in a Distance Learning Environment

As increasing numbers of educational institutions implement distance learning (DL) programs, educators need to know how teaching and learning processes change when teachers and learners are no longer in the same place at the same time. Understanding the theoretical and practical implications of these changes can help teachers to compensate learners for the limitations that often characterize a DL environment. In this article, we describe how we used content analysis to identify how university lecturers' verbal and nonverbal dialogue patterns changed when they taught in both conventional and DL environments. Data, indicating significant cross-context changes in teacher-student interaction patterns, validate Moore's (1972, 1993) transactional distance theory. This theory predicts that the increased psychological and communicative space, which needs to be crossed in a DL environment, has a potentially negative effect on teaching and learning. Empirical evidence of changes in specific categories of interactio...

An Integrated Analysis of Verbal and Nonverbal Interaction in Conventional and Distance Learning Environments

This study examines the relationship between the level of risk-taking among Israeli elementary school teachers and their attitude towards the use of computers within the framework of Computer-Assisted Instruction (CAI). The teachers in the research sample responded to two questionnaires-risk-taking questionnaire and attitude towards computers questionnaire. One factor-risktaking behaviour-was yielded from the first questionnaire and one factor-computer related attitude-was yielded from the second.



An analysis of the data obtained in the study indicates that teachers who are high-level risk-takers are more positive towards the use of computers in their teaching activities than medium-level risktakers who in turn have a more positive attitude towards computer use within the framework of CAI than low-level risk-takers.

http://www.researchgate.net/profile/Yaacov_Katz2/publication/229814455_Computer_oriented_attitudes_as_a_function_of_risktaking_among_Israeli_elementary_school_teachers/links/00b49522c1cbae61fb000000.pdf

Baruch Offir

Papers

Surface and deep learning processes in distance education: Synchronous versus asynchronous systems

Teacher–student interactions and learning outcomes in a distance learning environment

Introverts, Extroverts, and Achievement in a Distance Learning Environment

An Integrated Analysis of Verbal and Nonverbal Interaction in Conventional and Distance Learning Environments

Computer oriented attitudes as a function of risk‐taking among Israeli elementary school teachers